Development and validation of an instrument to predict online student success using faculty perceptions

Distance learning is growing and transforming educational institutions. The increasing use of distance learning by higher education institutions and particularly community colleges coupled with the higher level of student attrition in online courses than in traditional classrooms suggests that increased attention should be paid to factors that affect online student course completion. The purpose of the study was to develop and validate an instrument to predict community college online student course completion based on faculty perceptions, yielding a prediction model of online course completion rates. Social Presence and Media Richness theories were used to develop a theoretically-driven measure of online course completion. This research study involved surveying 311 community college faculty who taught at least one online course in the past 2 years. Email addresses of participating faculty were provided by two south Florida community colleges. Each participant was contacted through email, and a link to an Internet survey was given. The survey response rate was 63% (192 out of 303 available questionnaires). Data were analyzed through factor analysis, alpha reliability, and multiple regression. The exploratory factor analysis using principal component analysis with varimax rotation yielded a four-factor solution that accounted for 48.8% of the variance. Consistent with Social Presence theory, the factors with their percent of variance in parentheses were: immediacy (21.2%), technological immediacy (11.0%), online communication and interactivity (10.3%), and intimacy (6.3%). Internal consistency of the four factors was calculated using Cronbach's alpha (1951) with reliability coefficients ranging between .680 and .828. Multiple regression analysis yielded a model that significantly predicted 11% of the variance of the dependent variable, the percentage of student who completed the online course. As indicated in the literature (Johnson & Keil, 2002; Newberry, 2002), Media Richness theory appears to be closely related to Social Presence theory. However, elements from this theory did not emerge in the factor analysis.

Development of an instrument to measure high school students' global awareness and attitudes: Looking through the lens of social sciences

The purpose of this study was to develop an instrument to measure high school students’ perspectives on global awareness and attitudes toward social issues. The research questions that guided this study were: (a) Can acceptable validity and reliability estimates be established for an instrument developed to measure high schools students' global awareness? (b) Can acceptable validity and reliability estimates be established for an instrument developed to measure high schools students' attitudes towards global social issues? (c) What is the relationship between high school students’ GPA, race/ethnicity, gender, socio-economic status, parents’ education, getting the news, reading and listening habits, the number of classes taken in the social sciences, whether they speak a second language, and have experienced living in or visiting other countries, and their perception of global awareness and attitudes toward global social issues. ^ An ex post facto research design was used and the data were collected using a 4-part Likert-type survey. It was administered to 14 schools in the Miami-Dade County, Florida area to 704 students. A factor analysis with an orthogonal varimax rotation was vii used to select the factors that best represented the three constructs – global education, global citizenship, and global workforce. This was done to establish construct validity. Cronbach’s alpha was used to determine the reliability of the instrument. Descriptive statistics and a hierarchical multiple regression were used for the demographics to establish their relationship, if any, to the findings. ^ Key findings of the study were that reliable and valid estimates can be developed for the instrument. The multiple regression analysis for model 1 and 2 accounted for a variance of 3% and 5% for self-perceptions of global awareness (factor 1). The regression model also accounted for a 5% and 13% variance in the two models for attitudes toward global social issues (factor 2). The demographics that were statistically significant were: ethnicity, gender, SES, parents’ education, listening to music, getting the news, speaking a second language, GPA, classes taken in the social sciences, and visiting other countries. An important finding for the study was those attending public schools (as opposed to private schools) had more positive attitudes towards global social issues (factor 2) The statistics indicated that these students had taken history, economics, and social studies – a curriculum infused with global perspectives.^

A Q factor analysis of college undergraduate students' study behaviors

The purpose of this study was to better understand the study behaviors and habits of university undergraduate students. It was designed to determine whether undergraduate students could be grouped based on their self-reported study behaviors and if any grouping system could be determined, whether group membership was related to students’ academic achievement. A total of 152 undergraduate students voluntarily participated in the current study by completing the Study Behavior Inventory instrument. All participants were enrolled in fall semester of 2010 at Florida International University. The Q factor analysis technique using principal components extraction and a varimax rotation was used in order to examine the participants in relation to each other and to detect a pattern of intercorrelations among participants based on their self-reported study behaviors. The Q factor analysis yielded a two factor structure representing two distinct student types among participants regarding their study behaviors. The first student type (i.e., Factor 1) describes proactive learners who organize both their study materials and study time well. Type 1 students are labeled “Proactive Learners with Well-Organized Study Behaviors”. The second type (i.e., Factor 2) represents students who are poorly organized as well as being very likely to procrastinate. Type 2 students are labeled Disorganized Procrastinators. Hierarchical linear regression was employed to examine the relationship between student type and academic achievement as measured by current grade point averages (GPAs). The results showed significant differences in GPAs between Type 1 and Type 2 students at the .05 significance level. Furthermore, student type was found to be a significant predictor of academic achievement beyond and above students’ attribute variables including sex, age, major, and enrollment status. The study has several implications for educational researchers, practitioners, and policy makers in terms of improving college students' learning behaviors and outcomes.